Amazon SageMaker AI Projects now supports provisioning custom machine learning (ML) project templates from Amazon S3. Administrators can now manage ML templates in SageMaker AI studio so data scientists can create standardized ML projects to meet their organizational needs.
Data scientists can use Amazon SageMaker AI Projects to create standardized ML projects that meet organizational requirements and automate ML development workflows. Administrators define standardized ML project templates that include end-to-end development patterns. By provisioning custom templates from Amazon S3, administrators can define standardized project templates and provide access to these templates directly in the SageMaker AI studio for data scientists, ensuring all ML projects follow organizational standards.
SageMaker AI Projects custom template S3 provisioning is available in all AWS Regions where SageMaker AI Projects is available.
To learn more, visit SageMaker AI Projects documentation, and SageMaker AI Studio.
Categories: general:products/amazon-sagemaker,marketing:marchitecture/management-and-governance,marketing:marchitecture/artificial-intelligence
Source: Amazon Web Services
